Coworking Space Scraper — Amenities, Pricing & Ratings

Extract structured coworking space data from Coworker.com — amenities, pricing, ratings, desk types, and contact info — for any city or country worldwide.

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What does Coworking Space Scraper do?

Coworking Space Scraper automates the collection of coworking space listings from Coworker.com, the world's largest coworking directory with 20,000+ spaces across 170+ countries. It navigates search results pages, enqueues individual space profiles, and extracts structured data from each one — no manual copy-pasting, no login required.

Core capabilities:

• 🔍 Search by city or country — enter any location (e.g. "London", "New York", "Spain") and the scraper returns all matching spaces
• 🏷️ Amenity extraction — WiFi, Parking, Showers, 24/7 Access, Meeting Rooms, Printing, and more
• 💰 Pricing data — lowest price shown per space (daily, monthly, or weekly rates)
• ⭐ Ratings and reviews — star rating and total review count per space
• 🏢 Desk type detection — Hot Desk, Dedicated Desk, Private Office, Meeting Room, Virtual Office
• 📞 Contact info — phone number, external website, full address
• 🔢 Pagination — automatically follows result pages to reach your target volume

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What data can you extract?

Location & Identity

Field	Type	Example
📛 name	string	"The Office Group — Bloomsbury"
🔗 url	string	"https://www.coworker.com/space/..."
📍 address	string	"9–13 St Andrew St, London EC4A 3AF"
🏙️ city	string	"London"
🌍 country	string	"United Kingdom"

Workspace Details

Field	Type	Example
🛋️ amenities	array	["WiFi", "Coffee", "Parking", "Showers", "Lockers", "Printing"]
🖥️ deskTypes	array	["Hot Desk", "Dedicated Desk", "Private Office"]
⏰ openingHours	string	"Mon–Fri 8am–8pm"
👥 capacity	number	250

Pricing & Reviews

Field	Type	Example
💰 pricingFrom	string	"$15/day"
⭐ rating	number	4.7
💬 reviewCount	number	142

Contact

Field	Type	Example
🌐 website	string	"https://theofficegroup.com"
📞 phone	string	"+44 20 7123 4567"
📝 description	string	"A premium coworking space in the heart of London"

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Can I use Coworking Space Scraper to find spaces in any city or country?

Yes — Coworking Space Scraper works for any city or country covered by Coworker.com, which spans 170+ countries worldwide. Simply enter a location in the location field (e.g. "Tokyo", "Berlin", "Australia") and the scraper returns all listed spaces for that area. You can further narrow results by combining a location with optional keywords like "dog friendly" or "podcast studio", and filter output by required amenities using the amenityFilter field.

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How does Coworking Space Scraper work?

The Process

1. Start with a search URL — Coworking Space Scraper constructs a Coworker.com search query from your location (and optional keywords) input.
2. Load the results page — A headless Playwright browser opens the page and waits for JavaScript-rendered listing cards to appear.
3. Collect profile links — All links to individual space profiles (/space/...) are extracted from the search results.
4. Follow pagination — If there are more results pages, the scraper enqueues the next page and continues collecting links.
5. Visit each profile — For every space URL collected, the scraper opens the detail page and extracts all fields: name, address, amenities, pricing, ratings, hours, contact info, and description.
6. Filter and save — If an amenityFilter is set, spaces missing required amenities are dropped. Results are pushed to the dataset.

Think of it as having a research assistant who manually visits every Coworker.com listing in a city, copies all the details into a spreadsheet, and hands it back to you in seconds.

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Why use Coworking Space Scraper?

Feature	Manual Research	Coworking Space Scraper
Time to collect 100 spaces	3–5 hours	Under 10 minutes
Data consistency	Inconsistent, copy-paste errors	Structured JSON every time
Coverage	Limited by patience	Up to 500 spaces per run
Amenity filtering	Manual cross-checking	Built-in amenityFilter param
Scheduling	Impossible manually	Cron scheduling on Apify
Export to spreadsheet	Manual	One-click CSV/XLSX export
Integration with tools	None	Zapier, Make, n8n, Google Sheets, Slack

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What can you do with coworking space data after scraping?

Remote work research — Digital nomads and remote workers can compare hundreds of spaces across a city by price, amenities, and ratings before committing to a membership.

HR team scouting — HR teams at growing startups can identify coworking spaces with meeting rooms, parking, and 24/7 access that meet team requirements — across multiple cities at once.

Commercial real estate analysis — Real estate analysts can track coworking space density by neighbourhood, monitor pricing trends month over month, and benchmark operators against each other.

Cost-of-living comparisons — Researchers and journalists comparing cities for remote work can include coworking desk prices as a quantifiable data point alongside rent and transport costs.

Coworking price tracker — Operators and consultants can monitor competitor pricing regularly using scheduled runs, alerting on price changes via Make or Zapier.

Market analysis for operators — Coworking operators entering a new market can assess the competitive landscape: how many spaces exist, what amenities they offer, and their price positioning.

Shared office finder for tools and apps — Developers building remote work apps or tools can use Coworking Space Scraper to power a "find a space near me" feature or populate a database without maintaining a manual list.

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How to use Coworking Space Scraper?

1. Go to the Apify Store and open Coworking Space Scraper.
2. Click "Try for free" — you will be prompted to create a free Apify account if you don't have one.
3. Set your location — type a city, country, or region in the Location field (e.g. "Barcelona").
4. (Optional) Add keywords — narrow the search with a keyword like "podcast studio" or "dog friendly".
5. Set Max Results — start with 10–20 for a test run, then increase to 50–500 for a full export.
6. (Optional) Set amenity filters — add required amenities like "Parking" or "Showers" to the amenityFilter list.
7. Click "Save & Run" — the actor will start immediately. A typical run for 50 spaces takes 3–8 minutes.
8. Download your data — once complete, export as JSON, CSV, or Excel from the Dataset tab. Or connect to Google Sheets via integration.

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How much will it cost?

Coworking Space Scraper runs on Apify's pay-per-event model. You only pay for what you use.

• Free tier — Apify's $5/month free credit covers approximately 500–1,000 spaces per month depending on page complexity.
• Typical run cost — scraping 50 spaces costs roughly $0.05–0.15 depending on page load time.
• Cost tips:
  • Keep maxResults low for test runs (use 10)
  • Schedule recurring runs during off-peak hours
  • Use the amenityFilter to only save relevant spaces, reducing wasted compute
  • Proxy usage is not required for Coworker.com under normal conditions

See Apify pricing for full details.

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⬇️ Input

Field	Type	Required	Default	Description
location	string	Yes	—	City, country, or region to search (e.g. "London", "New York", "Spain")
keywords	string	No	—	Optional keyword filter (e.g. "podcast studio", "dog friendly")
maxResults	integer	No	50	Max number of spaces to return. Min 1, max 500
amenityFilter	array	No	[]	Only return spaces with ALL of these amenities (e.g. ["Parking", "Showers"])

Example 1 — Basic city search

{
  "location": "London",
  "maxResults": 50
}

Example 2 — Filtered search with amenity requirements

{
  "location": "New York",
  "keywords": "rooftop",
  "maxResults": 100,
  "amenityFilter": ["Parking", "24/7 Access", "Showers"]
}

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⬆️ Output

Each item in the dataset represents one coworking space with the following fields:

Field	Type	Description
name	string	Space name
url	string	Coworker.com profile URL
address	string / null	Full street address
city	string / null	City
country	string / null	Country
amenities	array	List of amenity strings
deskTypes	array	Types of workspace available
pricingFrom	string / null	Lowest price shown (e.g. "$15/day")
rating	number / null	Star rating (0–5)
reviewCount	number / null	Total number of reviews
capacity	number / null	Total seats or desks
openingHours	string / null	Operating hours
website	string / null	Space's own website
phone	string / null	Contact phone number
description	string / null	Short description or tagline

Example output item

{
  "name": "The Office Group — Bloomsbury",
  "url": "https://www.coworker.com/space/united-kingdom/london/the-office-group-bloomsbury",
  "address": "9–13 St Andrew St, London EC4A 3AF",
  "city": "London",
  "country": "United Kingdom",
  "amenities": ["WiFi", "Coffee", "Printing", "Meeting Rooms", "Showers", "Lockers", "24/7 Access"],
  "deskTypes": ["Hot Desk", "Dedicated Desk", "Private Office", "Meeting Room"],
  "pricingFrom": "£25/day",
  "rating": 4.7,
  "reviewCount": 142,
  "capacity": 250,
  "openingHours": "Mon–Fri 8am–8pm",
  "website": "https://theofficegroup.com",
  "phone": "+44 20 7123 4567",
  "description": "A premium coworking and flexible office space in the heart of London's legal district."
}

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Are there other tools in the Apify Store?

If you're doing broader research on locations, businesses, or market opportunities, these actors from the same library may help:

• Michelin Restaurant Finder — scrape Michelin Guide restaurant data by city or region, including star ratings, cuisine types, and contact info. Useful for pairing coworking location analysis with local dining options.

• City Event Feed Scraper — extract upcoming local events by city. Useful for coworking operators running community event calendars or digital nomads planning trips around local events.

• Shopify Store Finder — discover Shopify stores by niche and country. Useful for startup founders and e-commerce teams scouting for office space near relevant business clusters.

• Keyword Opportunity Finder — find low-competition keyword opportunities in your niche. Useful for coworking operators looking to improve their SEO and drive organic signups.

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Frequently Asked Questions

Can I scrape coworking spaces in any city or country?

Yes. Coworking Space Scraper works for any location available on Coworker.com, which covers 170+ countries including the United States, United Kingdom, Germany, Australia, Japan, Brazil, and more. Enter a city name (e.g. "Sydney"), a country (e.g. "Germany"), or a region (e.g. "Southeast Asia") in the location field.

How many coworking spaces can I scrape per run?

You can scrape up to 500 spaces per run using the maxResults parameter. For larger datasets — for example if you need all coworking spaces across a whole country — run the actor multiple times with city-level queries and merge the outputs. A single run of 50 spaces typically completes in 3–8 minutes.

Can I filter by amenities like parking or showers?

Yes. Use the amenityFilter input to specify a list of required amenities (e.g. ["Parking", "Showers", "24/7 Access"]). Only spaces that match all of the specified amenities will be included in your output dataset.

How often should I schedule runs?

For a coworking price tracker or shared office finder, a weekly schedule is usually sufficient since space listings and prices change slowly. For competitive monitoring, bi-weekly is a good balance between freshness and cost. You can set up a schedule directly in the Apify console under the "Schedules" tab.

Can I get pricing data for coworking spaces?

Yes. The pricingFrom field contains the lowest price shown on each space's Coworker.com profile (e.g. "$15/day", "£200/month"). Note that not all spaces publicly list prices — when no price is shown, the field returns null. For full pricing tiers, visit the individual space profile.

What if the scraper doesn't find results for my city?

If results are sparse, try broader search terms — use the country name instead of the city, or remove keywords. Some smaller cities have very few listings on Coworker.com. You can also try alternative spellings or English transliterations of city names (e.g. "Munich" instead of "München").

Can I use integrations with Coworking Space Scraper?

Yes. Coworking Space Scraper integrates with any tool that supports Apify webhooks or the Apify API. Popular integrations include:

• Google Sheets — export results directly to a spreadsheet
• Zapier — trigger workflows when a run completes
• Make (Integromat) — connect to 1,500+ apps
• n8n — build open-source automation workflows
• Slack — post new coworking space results to a channel

All integrations are available from the Apify console under "Integrations".

Can I use Coworking Space Scraper with the Apify API?

Yes. Every actor on Apify has a full REST API. You can start a run, pass input parameters, poll for status, and retrieve dataset items programmatically. See the Apify API documentation for full details. Example endpoint to start a run:

POST https://api.apify.com/v2/acts/TroveVault~coworking-space-scraper/runs
Authorization: Bearer YOUR_API_TOKEN

Can I use Coworking Space Scraper through an MCP Server?

Yes. Apify supports the Model Context Protocol (MCP), which lets AI assistants like Claude access and run actors directly. You can connect Coworking Space Scraper to any MCP-compatible client and ask it to "find all coworking spaces in Berlin with parking and showers" — the actor will run and return structured results. See Apify MCP documentation for setup instructions.

Is scraping Coworker.com data legal?

Scraping publicly available directory data for research and analysis purposes is generally permitted. Coworker.com listings are accessible to anyone without logging in, and extracting this publicly displayed information is comparable to reading and recording it manually. You should not use the data to republish a competing directory, misrepresent the source, or violate Coworker.com's terms of service. For commercial use cases, review the site's terms and consult legal counsel if needed. Coworking Space Scraper does not bypass any authentication, access controls, or paywalls.

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Your feedback

Have a feature request, found a bug, or want to request support for a new site? Open an issue on the Issues tab of this actor's Apify page. All feedback is read and acted on.